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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

The topography of Ganymede's grooved terrain

Using the technique of photoclinometry, topographic profiles across areas of grooved terrain and several other features on Ganymede have been constructed. The grooved terrain examined consists of subparallel grooves spaced 3-10 km apart. Topographic amplitudes are typically 300-400 m, with a maximum of about 700 m. Slopes are very gentle and tend to be primarily concave upward. Very few major positive relief features exist on Ganymede. The most important of these is a broad, gently sloping dome-shaped feature 260 km in diameter and over 2 km high.

Squyres, S. W.↗
NASA NTRS2000

Evolution and Mean Properties of Convective Systems in Southwestern Amazonia During TRMM-LBA

During the wet season TRMM field campaign in Rondonia, Brazil, a variety of convective systems were sampled by radar, sounding, and geostationary satellite for a 60 day period in early 1999. Local variations in the local wind and humidity field have been attributed in part by this study to synoptic scale phenomena, most conspicuously the establishment of stationary frontal systems penetrating into the tropics. These baroclinic systems induced periodic episodes low level moist, westerly flow across Rondonia during the experiment. This flow feature may be an important component of the South American climate system by playing a role in maintaining the South Atlantic Convergence Zone, which was active during these local westerly wind events. It is therefore important to understand the differences in mesoscale properties of convective systems between the westerly wind periods and intervening easterly wind periods. Differences in shear and moisture characteristics (Halverson et al. 2000, this meeting) are compared to structural and life-cycle characteristics of convective systems in Rondonia. Data from ground based radar and geostationary satellite provide a view of the evolution of the vertical structure and horizontal morphology of several large mesoscale convective systems in each regime. Preliminary statistics on the diurnal variation of precipitation intensity, areal coverage, and cloud top area are presented. Results suggest that long-lived, shallow convective systems with a large stratiform component of precipitation are characteristic of the westerly wind periods. A goal of this study is to establish a basis for which to parameterize the mesoscale effects of convection on large scale features of the South American climate system.

Rickenbach, Thomas M.↗
DOE OSTI2023

Agilent CRADA (Abstract)

The CRADA between Agilent Technologies Inc. and Battelle will focus on five software components as listed below: Prototype 4D Feature Finding functionality with a particular focus on recovering low level features and extending the bottom end dynamic range of IM-MS technology. Compare and contrast developments to current 4D Feature Finding capabilities. Highlight important algorithmic aspects employed. Implement the PNNL saturation correction algorithm. Agilent will give PNNL the needed data file access API and assistance in understanding it implementation and any needed instrumental aspects. Supported high resolution products to include Agilent’s TOF, QTOF and IM-QTOF mass spectrometers. PNNL will then work with Agilent to benchmark performance. Implementation of the PNNL Hadamard de-multiplexing algorithm. Agilent will give provide PNNL the needed date file access API access and as needed assistance in understanding the current Agilent multiplexed IM offering. PNNL will then work with Agilent on benchmark performance. Add ion mobility collision cross sections to existing and new metabolomic libraries for data analysis with Agilent’s informatics program MPP/ID Browser. PNNL will work with Agilent to create a software pipeline that takes data from chemical and metabolic standards and properly formats it for inclusion in MPP accessible libraries, using the collision cross section as a new separation dimension. Improvements of MPP multidimensional matching to identify metabolomic features using multiple characteristics beyond retention time and accurate mass. Most significantly matching will include analyte collision cross section with proposed support for sample fraction or RapidFire cartridge and fragmentation spectra. PNNL will work with Agilent to modify and improve the current MPP analysis pipeline to allow for creating, aligning, and identifying MS features defined by accurate mass, collision cross section and chromatographic retention time. As additional criteria such as fraction or RapidFire cartridge type are supported in the identification process, then they also will become part of the automation workflow. This includes the automation of said system to work with command line program (i.e. not a GUI) sufficient for programmatic execution in a pipeline.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Preliminary large-eddy simulations of flow around a NACA 4412 airfoil using unstructured grids

Large-eddy simulation (LES) has matured to the point where application to complex flows is desirable. The extension to higher Reynolds numbers leads to an impractical number of grid points with existing structured-grid methods. Furthermore, most real world flows are rather difficult to represent geometrically with structured grids. Unstructured-grid methods offer a release from both of these constraints. However, just as it took many years for structured-grid methods to be well understood and reliable tools for LES, unstructured-grid methods must be carefully studied before we can expect them to attain their full potential. In the past two years, important building blocks have been put into place making possible a careful study of LES on unstructured grids. The first building block was an efficient mesh generator which allowed the placement of points according to smooth variation of physical length scales. This variation of length scales is in all three directions independently, which allows a large reduction in points when compared to structured-grid methods, which can only vary length scales in one direction at a time. The second building block was the development of a dynamic model appropriate for unstructured grids. The principle obstacle was the development of an unstructured-grid filtering operator. In the past year, some of the new filters developed by Jansen have been implemented into a highly parallelized finite element code based on the Galerkin/least-squares finite element method. We have chosen the NACA 4412 airfoil at maximum lift as the first simulation for a variety of reasons. First, it is a problem of significant interest since it would be the first LES of an aircraft component. Second, this flow has been the subject of three experimental studies. The third reason for considering this flow is the variety of flow features which provide an important test of the dynamic model. Only the dynamic model can be expected to perform satisfactorily in this variety of situations: from the laminar regions where it must not modify the flow at all to the turbulent boundary layers and wake where it must represent a wide variety of subgrid-scale structures. The flow configuration we have chosen is that of Wadcock (1987) at Reynolds number based on chord Re(sub c) = u(sub infinity)c/v = 1.64 x 10(exp 6), Mach number M = 0.2, and 12 deg angle of attack.

Jansen, Kenneth↗
DOE OSTI2023

How to GIWAXS: Grazing Incidence Wide Angle X‐Ray Scattering Applied to Metal Halide Perovskite Thin Films

Abstract The frequency of reports utilizing synchrotron‐based grazing incident wide angle X‐ray scattering (GIWAXS) to study metal halide perovskite thin films has exploded recently, as this technique has proven invaluable for understanding several structure‐property relationships that fundamentally limit optoelectronic performance. The GIWAXS geometry and temporal resolution are also inherently compatible with in situ and operando setups (including ISOS protocols), and a relatively large halide perovskite research community has deployed GIWAXS to unravel important kinetic and dynamic features in these materials. Considering its rising popularity, the aim here is to accelerate the required learning curve for new experimentalists by clearly detailing the underlying analytical concepts which can be leveraged to maximize GIWAXS studies of polycrystalline thin films and devices. Motivated by the vast range of measurement conditions offered, together with the wide variety of compositions and structural motifs available (i.e., from single‐crystal and polycrystalline systems, to quantum dots and layered superlatices), a comprehensive framework for conducting effective GIWAXS experiments is outlined for different purposes. It is anticipated that providing a clear perspective for this topic will help elevate the quality of future GIWAXS studies—which have become routine—and provide the impetus required to develop novel GIWAXS approaches to resolve unsettled scientific questions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Numerical investigation of multiphase flow through self-affine rough fractures

Multiphase flow through fractures has great significance in subsurface energy recovery and gas storage applications. Different fracture and flow properties affect flow through a fracture which is difficult to control in laboratory experiments. Here, we perform lattice Boltzmann simulations in an ensemble of synthetically generated fractures. Drainage simulations are performed at different capillary numbers, wettability, and viscosity ratios. We track the invading front and quantify breakthrough saturations and show that roughness and wettability have a strong effect on fluid invasion through a complex fracture. Invading a more viscous fluid results in more stable displacement regardless of the capillary number while at very low capillary numbers, fluid migration is dependent on the inherent structure of the fracture. We develop a fluid displacement phase diagram in a single rough fracture and compare our results from that in the literature. Finally, we extend the phase diagrams across multiple fractures and demonstrate the importance of natural fracture features of roughness and wettability in identifying stable versus unstable displacement regimes during multiphase flow through rough fractures. Our work presents an end-to-end numerical pathway for testing on experimental data and expanding numerical data sets for testing combinations of different physical phenomenon and make valuable predictions on fluid flow through rough fractures.

02 PETROLEUM↗
DOE OSTI2020

Brachiopod δ 34 S CAS microanalyses indicate a dynamic, climate-influenced Permo-Carboniferous sulfur cycle

Early isotopic studies of sulfate in carbonate minerals (carbonate associated sulfate; CAS) suggested that carbonates can provide a reliable, well-dated archive of the marine sulfur cycle through time. However, subsequent research has shown that diagenetic alteration can impose highly heterogeneous CAS sulfur isotopic compositions (δ 34 S CAS ) among different carbonate phases within sediments. Such alteration necessitates targeted sampling of well-preserved, primary carbonate phases. Here, we present a new record of Carboniferous and Early Permian brachiopod δ 34 S CAS generated from over 130 measurements of microsampled brachiopod shells. Our record refines existing brachiopod δ 34 S CAS records and confirms a large, ~6.5‰ δ 34 S CAS decrease in the Early Carboniferous. Importantly, the record also features a novel 3–5‰ increase in δ 34 S CAS near the Serpukhovian-Bashkirian boundary (323.4 Ma) that coincides with carbonate δ 13 C and δ 18 O increases. Variability in δ 34 S CAS is minor both within (≤0.3‰) and among (≤2‰) individual co-depositional brachiopod specimens. A taxon-specific δ 34 S CAS offset is present one species (Composita subtilita) that also exhibits a δ 13 C offset, supporting the existence of biological “vital effects” on δ 34 S CAS . Geologic evidence and mathematical modeling of the Permo-Carboniferous carbon and sulfur cycles suggest that changes in the burial ratio of organic carbon to pyrite sulfur (R C:S ) are insufficient to explain the observed mid-Carboniferous δ 34 S CAS record. We find that changes in the 34 S depletion of pyrite relative to seawater sulfate ( 34 ε) or in the δ 34 S of the input to the ocean (δ 34 S in ) are also needed. Large additions of O 2 from organic carbon burial during the Permo-Carboniferous cannot be entirely compensated for with sulfur cycle changes; lower than modern late Visean pO 2 and/or additional O 2 sinks are needed to keep pO 2 at plausible levels. Based on the geologic context surrounding our record's mid-Carboniferous δ 34 S CAS increase, we advocate for simultaneous changes in pyrite burial, 34 ε, and δ 34 S in , driven by sea level or tectonically induced changes in environments of sulfur burial, as a viable mechanism to produce rapid seawater δ 34 S changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Interpreting omics data with pathway enrichment analysis

Pathway enrichment analysis is indispensable for interpreting omics datasets and generating hypotheses. However, the foundations of enrichment analysis remain elusive to many biologists. Here, in this study, we discuss best practices in interpreting different types of omics data using pathway enrichment analysis and highlight the importance of considering intrinsic features of various types of omics data. We further explain major components that influence the outcomes of a pathway enrichment analysis, including defining background sets and choosing reference annotation databases. To improve reproducibility, we describe how to standardize reporting methodological details in publications. This article aims to serve as a primer for biologists to leverage the wealth of omics resources and motivate bioinformatics tool developers to enhance the power of pathway enrichment analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Photoreversible Color-Switching Cu-Doped TiO2 Nanoparticles for High-Contrast Rewritable Printing

Light-printable rewritable paper that can be used multiple times has attracted extensive attention because of its potential benefits in reducing environmental pollution and energy consumption. Developing rewritable paper with high black-to-colorless contrast, lasting legibility, and a fast response is fascinating but challenging. Here, we integrate the redox chemistry of Cu2+ ions into photoreductive TiO2 nanoparticles to produce Cu-doped TiO2 nanoparticles capable of highly photoreversible switching between colorless and black with excellent contrast and color stability. Incorporating such nanoparticles into hydroxyethyl cellulose produces a rewritable paper with the same appearance as that of conventional paper. More importantly, it demonstrates great features promising for practical applications, including high black-to-colorless contrast, fast light-printing (<20 s), long legible time (>3 days), high reversibility (>50 cycles), high resolution (90 μm), and large scale (A4 size) applicability.

Wang, Wenshou↗
DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗
DOE OSTI2021

Artificial neural network prediction of self-diffusion in pure compounds over multiple phase regimes

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge. First, an ANN was developed with the raw diffusion values to assess what the main drawbacks of this direct method were. The first approach for improving the predictions involved taking the log 10 of diffusion to provide a more uniform distribution and reduce the range of target output values used to develop the ANN. The second approach involved developing individual ANNs for each phase using the raw diffusion values. Results show that the log transformation leads to a model with the best self-diffusion constant predictions and an overall average absolute deviation (AAD) of 6.56%. The resultant ANN is a generalized model that can be used to predict diffusion across all three phases and over a diverse group of compounds. The importance of each input feature was ranked using a feature addition method revealing that the density of the compound has the largest impact on the ANN prediction of self-diffusion constants in pure compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas

One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The disruption event characterization and forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can lead to a disruption. Two different machine learning approaches are proposed to improve the ideal magnetohydrodynamic (MHD) no-wall limit component of the kinetic stability model included in DECAF. First, a random forest regressor (RFR), was adopted to reproduce the DCON computed change in plasma potential energy without wall effects for a large database of equilibria from the national spherical torus experiment (NSTX). This tree-based method provides an analysis of the importance of each input feature, giving an insight into the underlying physics phenomena. Secondly, a fully-connected neural network has been trained on sets of calculations with the DCON code, to get an improved closed form equation of the no-wall β limit as a function of the relevant plasma parameters indicated by the RFR. The neural network has been guided by physics theory of ideal MHD in its extension outside the domain of the NSTX experimental data. The estimated value has been incorporated into the DECAF kinetic stability model and tested against a set of experimentally stable and unstable discharges. Moreover, the neural network results were used to simulate a real-time stability assessment using only quantities available in real-time. Finally, the portability of the model was investigated, showing encouraging results by testing the NSTX-trained algorithm on the mega ampere spherical tokamak (MAST).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Understanding Majorana braiding in superconductors with a fixed total number of particles

Mean-field one-dimensional topological superconductors host edge Majorana zero modes (MZMs) that encode a topologically protected ground-state degeneracy and enable robust braiding operations within this subspace. Mean-field states lack definite particle number and thus cannot represent isolated systems. Nevertheless, projecting them onto fixed particle number can yield good approximations to an isolated superconductor ground state. In earlier work [Sajith et al., Phys. Rev. B 109, 184509 (2024)] we showed that the projected Kitaev wave function of a single wire preserves some important mean-field features, such as the zero-energy spectral peaks near the wire edges. However, uniqueness of the fixed-number ground state does not allow for any nontrivial operations in the ground-state subspace. To overcome this limitation, here we consider the case of multiple wires with a conserved total charge, using the same approach. In the limit of vanishing interwire coupling, this system has a macroscopic ground-state degeneracy. We show how this degeneracy is resolved by coherent single-particle tunneling, and identify special many-body states which play the same role as the MZM parity states in the mean field. In this work, we demonstrate how braiding operations can be implemented and discuss both intrinsic and extrinsic limits on their fidelity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Synthesis and functionalization of electron-deficient perfluoroalkyl porphyrin building blocks for supermolecular systems

Synthetic strategies for electron-deficient meso-perfluoroalkylporphyrins bearing diverse functional groups are described. Scalable and efficient syntheses for 5-triisopropylsilylethynyl-10,15,20-tris(heptafluoropropyl)porphyrin and 5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphyrin that equip meso-ethynyl functional groups via the bilane route have been established, along with a refined route to [5,15-bis(heptafluoropropyl)porphinato]zinc(II). meso-Position halogenation of [5,15-bis(heptafluoropropyl)porphinato]zinc(II) was achieved by selective meso-nitration and subsequent reduction, diazonium salt formation, and iodination reactions. Computational data describe the low energy excited states of these chromophores and the electronic structural factors that control reactivity of these meso-perfluoroalkyl substituted porphyrin complexes. meso-Functionalized [5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphinato]zinc(II) and [5-iodo-10,20-bis(heptafluoropropyl)porphinato]zinc(II) building blocks lay the foundation for the construction of highly conjugated multiporphyrin arrays that feature electronic structural properties important for the development of n-type materials and high potential photooxidants.

Chemistry↗
DOE OSTI2024

Chemical and architectural intricacy from nanoscale tetrahedra and their analogues

The tetrahedron, as the simplest platonic shape, is a profound building block with the potential to create intricate superstructures. Noteworthy designs utilizing tetrahedral building blocks include the Sierpiński tetrahedron (the most fundamental three-dimensional fractal), a one-dimensional helical structure known as the tetrahelix, and various crystalline and quasicrystalline packings. Historically, the practicality of tetrahedral superstructures has been evident, providing stable, well-defined frameworks for various constructions, including truss bridges, tower cranes, and electricity transmission line pylons. In the field of self-assembled nanocrystal superlattices, tetrahedral nanocrystals, as building blocks, occupy a unique place among all the possible nanoscale particles. Mathematical models, simulation work, and experimental studies using nanocrystals in the laboratory have suggested that self-assembled structures derived from nanoscale tetrahedral building blocks are notably intricate, giving rise to new horizons of high-entropy nanocrystal superlattices. An important implication from previous works is that such tetrahedral nanocrystal superlattices form through highly delicate interparticle interactions, emphasizing the importance of the fine features of these nanocrystals. In this article, we summarize the advances in superlattices assembled from tetrahedral nanocrystals. Here, we first define the tetrahedron and tetrahedron analogues based on Conway’s transformation and graph theory, underscoring their relevance to the crystallization process producing tetrahedral nanocrystals. Then, we showcase previous reports on the synthesis of tetrahedral nanocrystals and the resulting nanocrystal superstructures. Finally, we conclude by offering insights and perspective into the chemical and architectural intricacy that could emerge from tetrahedral nanocrystals.

Nanostructure↗
DOE OSTI2019

Understanding Transient Combustion Phenomena in Low-NO x Gas Turbines

The goal of this work was to understand, quantify, and eventually predict combustion instability during operational transients in low-NO x gas turbine combustors. Transient operation is defined as a mode where one or more key operating parameters, including equivalence ratio, fuel composition, or fuel splitting between nozzles in a combustor, are varying in time. The timescale over which this variation occurs will be referred to as the transient timescale, the magnitude of the change in the transient parameter will be referred to as the transient amplitude, and the direction of the variation will be referred to as the transient direction. Transients occur regularly in power generation gas turbine operation. For example, load-following gas turbines vary load to meet power demands while accounting for variation in unsteady grid contributors like wind and solar power. Operators achieve this by varying equivalence ratio and fuel splitting inside the combustors to produce more or less power. Another example of transient operation is during fuel-switching operations, a particular issue for turbines operating with syngas fuels in a co-generation facility. In this case, the composition of the fuel stream may vary in time either as a result of fluctuations in the pipeline, or in the case of a co-generation plant, variations in feedstock or gasification processes. This fluctuation in fuel composition can have significant implications for combustion processes, particularly with high-hydrogen fuels. A small number of studies have investigated transient behavior in gas turbine combustors, particularly in the context of flame blow-off; here, investigators have typically focused on issues of transient amplitude, though without the depth and physics-based experimental design that is proposed in this program. To our knowledge, there have been no studies that have quantified the impact of the transient timescale on combustion. The work helped us understand the impact of several types of transients on combustion stability. Both static and dynamic combustion stability will be considered. The transients will be quantified using their amplitude, direction, and timescale, and we will consider transients in equivalence ratio, fuel composition, and fuel splitting. There were two main objectives of this work: 1. Provide a fundamental understanding of combustion stability during transient operation using data obtained from a number of high-speed diagnostic techniques on experimental configurations that capture important gas turbine combustor features and operating conditions. This goal was met in conjunction with our industrial partner, GE Global Research, with whom we worked closely throughout the program. 2. Develop a stability prediction framework that will allow for the prediction, and possible control, of instabilities as a function of the transient amplitude, direction, and timescale. This input/output model should be physics-based and allow for screening of operating conditions and prediction of unstable behavior at the end of a transient by monitoring combustor health and precursor signals during operation.

03 NATURAL GAS↗
DOE OSTI2023

Discerning Deception: An Empirically-Driven Agent-Based Model of Expert Evaluation of Scientific Content

Both human subject experiments and computational, modeling and simulations have been used to study detection of deception. This work aims to combine these two methods by integrating empirically-derived information (from human subject experiments) into agent-based models to generate novel insights into the complex problems of detection of disinformation content. Computational experiments are used to simulate across multiple scenarios for evaluation and decision-making regarding the validity of potentially deceptive scientific documents. Factors influencing the human agent behaviors in the model were identified through a human subject experiment that was conducted to evaluate and characterize decision making related to disinformation discernment. Correlation and regression analyses were used to translate insights from the human subjects experiment to inform the parameterization of agent features and scenario development. Three scenarios were evaluated with the agent-based models to help evaluate the replicability of the simulations (validation analysis) and assess the influence of human agent and document features (sensitivity analyses). A replication of the human participant experiment demonstrated that the agent-based simulations compare favorably to empirical findings. The agent-based modeling was then used to conduct sensitivity analysis on the accuracy of deception detection as a function of document proportions and human agent features. Results indicate that precision values are adversely impacted when the proportion of deceptive documents is lower in the overall sample, whereas recall values are more sensitive to changes in human agent features. These findings indicate important nuances in accuracy evaluations that should be further considered (including consideration of potential alternate metrics) in future agent-based models of disinformation. Additional areas for future exploration include extension of simulations to consider other ways to align the agent-based model design with psychological theory and inclusion of agent-agent interactions, especially as it pertains to sharing of scientific information within an organizational context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Advancing Tunnel Detection Via Vertical Acoustic Profiling

This study demonstrates that placing an acoustic source at depth significantly enhances the detection of tunnels. By adapting the methodology of vertical seismic profiling to acoustic-range frequencies, we introduce a novel approach for tunnel detection. To our knowledge, this report documents the first application of this technique. The field study was conducted on a cleared site at the Oak Ridge National Laboratory; the subsurface was clay. A series of vertical shafts were bored immediately before and after the placement of a 40 ft long, 3 ft diameter steel pipe located 10 ft below the surface. Acoustic signatures were produced at various depths up to 30 ft and an array of surface geophones was used to collect the resulting signals. The innovation lies in using subsurface acoustic signatures to better enable the collection of wide-angle diffracted waves by surface geophones. These diffracted waves appear as subharmonic frequencies of the source signal and are recorded by a surface geophone array. While the concept draws from vertical seismic profiling used in oil and gas exploration, a key distinguishing feature is the use of acoustic frequencies, which are necessary for detecting small subsurface features. The findings have important implications. Critical information pertaining to diffracted source signals are not measured by current state-of-the-art methods. Although this study confirms enhanced detectability, accurate localization and imaging will require additional research. Future work should focus on leveraging diffracted-wave strength and time delays to enable full imaging and characterization.

47 OTHER INSTRUMENTATION↗